New approach may prevent repeat of 2014-2015 debacle

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A novel method for predicting the evolution of circulating influenza mutations in the lab before they occur in nature has the potential to improve seasonal flu vaccine accuracy.

Note that the finding that genetic background can predict antigenic evolution holds promise for developing more accurate seasonal flu vaccines, but more studies are needed.

A novel method for predicting the evolution of circulating influenza mutations in the lab before they occur in nature has the potential to improve seasonal flu vaccine accuracy, researchers say.

Using samples of naturally occurring human H1N1 and H3N2 flu viruses from past flu seasons, the researchers were able to map mutational patterns that revealed virus clusters with unique mutations that matched the actual evolution of a future influenza outbreak.

"Our studies with contemporary human influenza viruses identified escape mutants before they caused an epidemic in 2014-2015," researcher Yoshihiro Kawaoka, PhD, of the University of Wisconsin-Madison School of Veterinary Medicine, and colleagues, wrote in Nature Microbiology, published online May 23.

The researchers are affiliated with the National Institutes of Health's Centers of Excellence for Influenza Research and Surveillance (CEIRS), which is working to lessen the impact of seasonal influenza internationally.

Changes in globally circulating flu strains are monitored annually and are now used to predict which strains to include in the next season's influenza vaccine. This strategy does not always produce an effective vaccine, however, as was the case during the 2014-2015 flu season, when the flu shot was determined to be largely ineffective.

The hemagglutinin (HA) protein is the major influenza viral antigen and the main target of infection-neutralizing antibodies, the researchers noted.

"During influenza virus circulation in humans, the antigenicity of the virus gradually changes due to mutations in the globular head of HA, necessitating frequent updates of the influenza vaccine," they wrote, adding that seasonal flu vaccine strains are currently selected "based on the antigenicity of clinical isolates and cross-reactive immunity in human populations in combination with genetic and epidemiologic data.

"This decision has to be made more than 6 months before the onset of the influenza season to allow sufficient time for vaccine manufacture," the team continued. "At the time of decision making, novel antigenic clusters may not have emerged or may not yet be recognized, occasionally resulting in the selection of vaccine strains that differ antigenically from the viruses circulating during the subsequent influenza season."

In their newly published study, Kawaoka and colleagues examine whether the antigenic evolution of human influenza A virus could be predicted using a strategy that included screening mutant virus libraries with random mutations in the antigenic region of HA with antisera against circulating viruses.

The researchers assembled libraries of human H1N1 and H3N2 viruses from sources that possessed various natural and random mutations in the HA protein.

Antigenic properties of the identified escape mutants were then analyzed using hemagglutination inhibition (HI) assay, and the mutation patterns were then mapped using a process known as antigenic cartography.

This mapping identified the clusters of viruses with novel mutations predictive of how H1N1 viruses in the 2009-2010 flu season and H3N2 in the 2014-2015 flu season actually evolved.

Animal studies in both mice and ferrets immunized against naturally occurring H1N1 influenza confirmed that the mutated viruses escaped detection by the immune system.

"Our pilot studies with past influenza viruses identified escape mutants that were antigenically similar to variants that emerged in nature, establishing the feasibility of our approach," the researchers wrote. "Our studies with contemporary human influenza viruses identified escape mutants before they caused an epidemic in 2014-2015."

Kawaoka and colleagues noted that their approach is "conceptually different" from current methods of predicting which circulating influenza variants will become dominant.

"Our method may therefore improve the current WHO influenza vaccine selection process," they said. "These in vitro selection studies are highly predictive of the antigenic evolution of H1N1 and H3N2 viruses in human populations. Hence, a limited number of experimental antigenic screens may be sufficient to identify potential future clusters."

The finding that genetic background can predict antigenic evolution holds promise for developing more accurate seasonal flu vaccines, but the researchers noted that for the method to be effective, "it will probably be necessary to keep the predictions up to date by reapplying the methodology as new clades emerge."

The research was supported by grants from the Bill & Melinda Gates Foundation, the National Institute of Allergy and Infectious Diseases, the Japan Science and Technology Agency, and the Japan Initiative for Global Research Network on Infectious Dseases.

Kawaoka and a co-author are founders of FluGen.

Reviewed by Robert Jasmer, MD Associate Clinical Professor of Medicine, University of California, San Francisco and Dorothy Caputo, MA, BSN, RN, Nurse Planner

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